Intelligent Vehicle Energy Analysis

NREL's intelligent vehicle energy analysis efforts forecast and inform future vehicle scenarios and illuminate how different decisions influence mobility, energy, and emissions.

Modeling and analysis activities enable fuel efficiency impact assessments that support NREL's cross-cutting transportation and mobility research. Because “off-cycle” technology benefits aren't revealed via lab tests, researchers employ innovative analysis capabilities to demonstrate and validate their real-world impacts.

Research and Development

Vehicle Sales Forecasting and Fuel Economy Modeling

How much do lower battery prices impact electric vehicle sales? How about fuel prices? What's the total cost of ownership for commercial electric vehicles? Researchers answer such questions as they consider the variables associated with forecasting consumer uptake of conventional and advanced vehicle technologies.

Using the Automotive Deployment Options Projection Tool (ADOPT), a vehicle consumer choice and stock model, researchers estimate the impact of vehicle technology improvements on future vehicle sales, energy use, and emissions based on the weighted value of key attributes such as vehicle price, fuel cost, acceleration, range, and availability.

ADOPT incorporates the Future Automotive Systems Technology Simulator (FASTSim), which compares vehicle powertrains and estimates the impact of technology improvements on vehicle efficiency, performance, cost, and battery life.

Additionally, researchers employ the Transportation Technology Total Cost of Ownership (T3CO) tool to assess the full life cycle costs of advanced technology commercial vehicles and evaluate the costs and savings associated with converting traditional diesel operations to electric.

Green Routing To Save Energy and Time

Leveraging NREL's world-class modeling and analysis capabilities, researchers partnered with Google to develop more eco-friendly routing in Google Maps. For more information, refer to the news article, Google Taps NREL To Incorporate Energy Optimization into Google Maps Route Guidance. Text version

Achieving maximum mobility with minimum energy consumption relies on understanding the energy costs associated with certain decisions. Employing the Route Energy Prediction Model (RouteE), researchers calculate the energy and time savings potential of specific green-routing options and analyze large-scale green-routing opportunities.

Merging vehicle simulation with real-world operation, NREL analysis predicts the energy consumption of a given vehicle over a proposed route and pinpoints the efficiency benefits of green routing while accounting for driving conditions such as anticipated traffic congestion, traffic speed, road type, number of lanes, road grade, and turns.

Such analyses enable researchers to co-optimize travel time and energy consumption for individual vehicles, fleets, and even entire transportation networks.

Optimized Fleet Management of Ride-Hailing Services

NREL's analysis of various considerations of interest to ride-hailing or mobility-service-provider fleets—including their charging infrastructure needs under future shared, automated, and electrified scenarios—sheds light on how fleet operations impact energy use, emissions, vehicle usage patterns, and service.

Using NREL's Highly Integrated Vehicle Ecosystem (HIVE) Framework, researchers simulate the operations of such fleets, comparing outcomes across scenarios that vary with respect to location, vehicle types, charging and fueling station networks, fleet operational behaviors, economic factors, and policy considerations.

Pathways for Achieving Transportation, Energy, and Environmental Objectives

Changes in transportation technologies, mode choices, and business models—such as those introduced by vehicle electrification, ride-hailing services, and micro-mobility solutions—are reshaping transportation energy demand.

Researchers use NREL's Transportation Energy and Mobility Pathway Options (TEMPO) Model to explore long-term pathways for reaching strategic objectives related to transportation, energy, and the environment. A transportation demand model, TEMPO characterizes opportunities for existing and future fuels, technologies, and business models across transportation sectors and segments and enables cross-sectoral integrated studies.

Real-World Data Informs Analyses

To assure the accuracy of their vehicle energy analyses, researchers tap into a wealth of real-world travel behavior data from the Transportation Secure Data Center along with commercial fleet vehicle operating data from the Fleet DNA clearinghouse.

Publications

The following publications provide detailed information about and examples of NREL's vehicle energy analyses.

RouteE: A Vehicle Energy Consumption Prediction Engine, SAE World Congress (2020)

Real-World Evaluation of National Energy Efficiency Potential of Cold Storage Evaporator Technology in the Context of Engine Start-Stop Systems, SAE World Congress (2020)

Understanding the Charging Flexibility of Shared Automated Electric Vehicle Fleets, SAE World Congress (2020)

Determining Off-Cycle Fuel Economy Benefits of 2-Layer HVAC Technology, SAE World Congress (2018)

FASTSim: A Model To Estimate Vehicle Efficiency, Cost, and Performance, SAE Technical Paper (2015)

ADOPT: A Historically Validated Light Duty Vehicle Consumer Choice Model, SAE Technical Paper (2015)

Contact

Contact us to learn more about our vehicle energy analysis capabilities or to discuss your partnership interests.

Eric Wood

Team Lead, Decarbonized Vehicle Systems

Eric.Wood@nrel.gov
303-275-3290